NONLINEAR CAUSALITY, with Applications to Liquidity and Stochastic Volatility
نویسنده
چکیده
1 Nonlinear Causality, with Applications to Liquidity and Stochastic Volatility Abstract The conditional Laplace transform is often easier to use in financial data analysis than the conditional density. This paper characterizes nonlinear causality hypotheses for models based on the conditional Laplace transform and provides interpretations of the linear and quadratic causality in this framework. The nonlinear causality conditions are derived for a multivariate volatility model that describes volatility transmission accross national stock markets, a bivariate count model for joint trading of assets and derivatives, and a stochastic volatility model in which the drift and volatility relation is examined.
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